Effect of Model-Eliciting Activities using Cloud Technology on the Mathematical Problem-Solving Ability of Undergraduate Students

Abstract

Problem-solving is considered as an important skill for learning Mathematics. Integration of cloud technology into Model-Eliciting Activities (MEAs) has been considered as an instructional approach to study students’ mathematical problemsolving abilities. The purposes of this study were to evaluate the suitability of the MEAs using cloud technology, and assess the mathematical problem-solving ability of undergraduate students learning the proposed model compared with the criteria of 50%. The participants were 50 undergraduate students who were enrolled on Numerical Analysis courses, selected by using a purposive sampling technique. We conducted quasi-experiments using a one-group design to determine the impact of the model on students and assessed whether the students had exceeded the criterion for mathematical problem-solving ability. The research instruments were instructional plans of the MEAs using cloud technology, a suitability assessment form, and a mathematical problem-solving test. The data were analysed quantitatively using descriptive statistics such as mean and standard deviation, and a t-test. The findings revealed that 5 experts evaluated the model as being “most suitable”, and that the mathematical problem-solving ability of the undergraduate students exceeded the criterion of 50% at a .05 level of statistical significance. The students displayed satisfactory competence in implementing key mathematical concepts to solve problems.